4.8 Article

Connecting multiple microenvironment proteomes uncovers the biology in head and neck cancer

期刊

NATURE COMMUNICATIONS
卷 13, 期 1, 页码 -

出版社

NATURE PORTFOLIO
DOI: 10.1038/s41467-022-34407-1

关键词

-

资金

  1. FAPESP [2009/54067-3, 2010/19278-0, 2016/07846-0, 2018/18496-6, 2015/19191-6, 2019/21815-9]
  2. CNPq [305851/2017-9, 310392/2021-7, 1190775]
  3. Brazilian Federal Government
  4. Center for Research in Energy and Materials (CNPEM), a private non-profit organization under the supervision of the Brazilian Ministry for Science, Technology, and Innovation (MCTI)
  5. Brazilian Biosciences National Laboratory (LNBio) [2009/53998-3]
  6. Laboratory for Integrative and System Biology (LaBIS) [2011/00417-3, 2015/50612-8]

向作者/读者索取更多资源

This study provides insights into the biology and potential biomarkers associated with metastasis in head and neck cancer through proteomic characterization and machine learning analysis.
The poor prognosis of head and neck cancer (HNC) is associated with metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision-making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identify nodal metastasis signatures in blood and saliva. We present a proteomic characterization wiring multiple sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures. The biological understanding of poor prognosis associated with lymph node metastasis in head and neck cancer (HNC) remains crucial. Here, a proteomic characterisation of 140 multisite samples from a 59-HNC patient cohort and machine learning reveals potential biomarkers and metastasis related signatures.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据